Spatially Differentiated Multi-Sectoral Mitigation Strategies Needed to Reduce PM2.5 Exposures in India
Year: 2026
Type: preprint
Abstract: Air pollution in India contributes to approximately 1 million deaths annually due to exposure to ambient fine particulate matter (PM 2.5 ). Here, we demonstrate that interventions to achieve the goals of India’s National Clean Air Program require adopting a multi-sector, multi-scale approach to link air pollution sources to human exposure. To support this objective, we developed PAVITRA (Air pollution management and intervention tool for India), a computationally efficient and high-fidelity air quality management tool. The tool integrates the InMAP reduced-complexity air quality model tailored for India, with the SMoG (Speciated Multi-pOllutant Generator)-COALESCE emissions inventory. By deploying over 2,000 simulations, we established how emissions from multiple sectors at different spatial scales contribute to PM2.5 throughout India. We find dissimilar emission drivers of PM 2.5 exposure at regional, state, and city scales, with especially large spatial differences in the relative contributions of domestic, agriculture, and transport sources. We also find that targeted state-level interventions may be nearly as effective as uniform nationwide strategies. These results highlight the limitations of one-size-fits-all policies. Rather, we demonstrate the value of coordinated but differentiated mitigation strategies at regional, state, and city jurisdictional scales for effective air quality management in India. Reduced-complexity modeling tools such as PAVITRA present a way forward to support rapid evaluation of sector and scale-specific mitigation strategies for effective, science-based policy development.
Source: ChemRxiv
Language: English
Subfield: Atmospheric Science
Field: Earth and Planetary Sciences
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7208721584